Name
Title | ||
|---|---|---|
A Kohonen-like Decomposition Method for the Traveling Salesman Problem: KNIESDECOMPOSE |
Abstract | ||
|---|---|---|
In addition to the classical heuristic algorithms of op- erations research there have also been several approaches based on artificial neural networks which solve the traveling salesman prob- lem (TSP). Their efficienc y, however, decreases as the problem size (number of cities) increases. An idea to reduce the complexity of a large-scale TSP instance is to decompose or partition it into smaller subproblems, which are easier to solve. In this paper we introduce an all-neural decomposition heuristic that is based on a recent self- organizing map called KNIES which has been successfully imple- mented in solving both the Euclidean TSP and the Euclidean Hamil- tonian path problem. |
Year | Venue | Keywords |
|---|---|---|
2000 | ECAI | decomposition method,heuristic algorithm,artificial neural network,traveling salesman problem,traveling salesman |
Field | DocType | Citations |
Bottleneck traveling salesman problem,Mathematical optimization,Heuristic,Computer science,Decomposition method (constraint satisfaction),Self-organizing map,Travelling salesman problem,Hamiltonian path problem,Artificial intelligence,2-opt,Artificial neural network,Machine learning | Conference | 3 |
PageRank | References | Authors |
0.41 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Necati Aras | 1 | 462 | 30.62 |
| I. Kuban Altinel | 2 | 150 | 14.60 |
| B. John Oommen | 3 | 1255 | 222.20 |